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dc.contributor.advisorCabrera-Ríos, Mauricio
dc.contributor.authorFont-Valentín, Amil A.
dc.description.abstractThe characterization of a disease through the detection of differentially expressed genes is of interest for early detection, diagnosis, prognosis, and prediction. Autism Spectrum Disorder (ASD) and Schizophrenia (SCZ) have been correlated in literature for sharing similar symptoms and behaviors, however, not at the genetic level. This work aims to correlate both conditions through the analysis of microarray datasets. Multiple Criteria Optimization was used to find the most significant gene expression changes common to both conditions. Thirty-six genes resulted from this first step. Subsequently, the most correlated structures were identified through the Traveling Salesman Problem and the Minimum Spanning Tree. Mathematical optimization, as a driver for gene selection and structuring, defines an analysis point of view advocated by our group that is different to biostatistics and bioinformatics. ASD and SCZ are analyzed simultaneously for the first time in this work owing to the capabilities of our group’s strategy.en_US
dc.subjectAutism Spectrum Disorderen_US
dc.subject.lcshDNA microarraysen_US
dc.subject.lcshMathematical optimizationen_US
dc.subject.lcshAutism Spectrum Disorderen_US
dc.subject.lcshDiseases -- Causes and theories of causationen_US
dc.titleGenetic commonalities of autism spectrum disorder and schizophreniaen_US
dc.rights.licenseAll rights reserveden_US
dc.rights.holder(c) 2019 Amil A. Font Valentínen_US
dc.contributor.committeeMéndez, Mayra
dc.contributor.committeeSeguel, Jaime
dc.contributor.representativeOrtíz, Gloribell Engineeringen_US
dc.contributor.collegeCollege of Engineeringen_US
dc.contributor.departmentDepartment of Industrial Engineeringen_US

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    Items included under this collection are theses, dissertations, and project reports submitted as a requirement for completing a graduate degree at UPR-Mayagüez.

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